Lots of quotes, fewer policies
Your quote journey is live. Marketing brings traffic. The dashboard shows a healthy number of quotes each day and a much smaller number of policies. The team has theories: the price is too high, the question set is too long, people are just browsing.
Nobody can say which is true, because analytics shows page views and your policy administration system shows quotes and policies, and the two are not joined. A customer who started a quote, hit a referral, came back two days later on a different device and bought appears as a lost quote and a new sale.
Where quote and bind journeys really break
In insurance the quote journey has failure points that ordinary checkout funnels do not.
| Step | What goes wrong | How it shows up |
|---|---|---|
| Eligibility questions | Wording people misread, answers that knock them out late | Drop-off after a specific question |
| Data enrichment calls | Address, vehicle or property lookups slow or failing | Long waits, error pages |
| Rating | Rating engine slow or returns a referral | Spinner, then an unclear message |
| Price shown | Price differs from what ads or aggregators suggested | Drop-off on the price page |
| Bind and payment | Price recalculated, payment fails, documents not generated | Errors at the last step |
Each step is often owned by a different part of the system, so no one sees the journey end to end.
The cost of quotes you never convert
Every quote you do not bind is acquisition spend with nothing to show for it. When the reason is technical, such as a lookup timing out, it is the most avoidable loss there is. Underwriting and pricing decisions get made on the assumption that price is the problem, when sometimes it is a question nobody understands. And people who were happy to buy but got stuck are left without a follow-up.
Instrumenting the journey and fixing what it shows
What we build joins journey data to your quote records and acts on what it finds.
- Each journey step sends an event, tied to the quote reference once one exists, so web analytics and your policy administration system tell one story.
- Response times and errors from rating and enrichment calls are recorded per quote.
- A funnel view shows where people stop, by channel, product and device, with the most common error or referral reason at each step.
- Referrals and declines are shown with the question that triggered them, so the underwriting team can decide whether wording or rules need looking at.
- Saved quotes are followed up by email with a link back to the same quote, where your rules and the customer's consent allow.
- Fixes are tested against the funnel, so you can see whether a change helped.
Changes to questions, rules or pricing remain your underwriting and pricing team's decisions. We give them the evidence and make the journey technically sound.
What the team sees afterwards
The weekly review looks at a funnel, not a total. The team can see that a particular lookup times out on mobile, that one eligibility question sends people away, or that most drop-off happens after a referral message. Engineering fixes the technical faults; underwriting reviews the wording. Customers who stopped get a way back to their quote.
Is your quote journey leaking like this?
- You know how many quotes you give but not where people stop.
- Analytics and your policy system are not joined.
- Rating or lookup errors are found in logs, not reports.
- Referral messages are generic.
- Saved quotes get no follow-up.